Diet plays a critical role in many health outcomes, from incidence of disease to quality of life to longevity itself. Most of the biological systems known to be influenced by diet and nutrition are involved in mediating the balance between growth, development, reproduction, and the response to stress. Dietary treatments, such as caloric restriction, and certain mutations, such as those involved in the insulin signaling pathway, are known to increase lifespan yet frequently yield negative effects on reproduction. The precise demographic consequences of these interventions are largely unknown, however. How any given individual will respond to a particular dietary regime depends on a complex combination of genetics, random environmental differences, and the systematic effects of the diet itself, leading to complex stochastic life trajectories for each individual. Understanding the functional basis of this complexity requires estimates of the demographic trajectories of numerous genetically identical individuals so that the entire distribution individual outcomes can be characterized and also requires a statistical framework that allows for the accumulation of individual differences to be attributed to the inherent properties-the stochastic kernel-of that individual. The model nematode Caenorhabditis elegans is especially amenable to addressing these problems because it has become a central player in understanding the genetic and physiological bases of stress response and aging and because it can be used to generated large numbers of genetically identical individuals for demographic analysis. Here, we propose: (1) to utilize innovative microfluidic and statistical approaches to precisely characterize individual demographic trajectories under different dietary inputs, (2) to examine the role of developmental state and insulin signaling and stress response pathways in mediating variation in reproductive patterns in the face of dietary fluctuations, and (3) to characterize the role of perception in dietary modulation of reproductive patterning. We will use custom designed microfluidic systems that (1) provide automated characterization of the reproductive dynamics of tens of thousands of individuals, (2) allow precise control of diet and food level, and (3) enable sorting of individuals based on physiological state, such levels of gene expression. A novel framework based on stochastic demography will be used to analyze the data in order to estimate individual stochastic kernels for natural isolates and longevity-related mutants reared under conditions of dietary restriction and exposure to naturally occurring nematode-associated bacteria. Perception deficient mutants will be used to distinguish modulation of reproduction driven by sensory input versus metabolic state. Taken together, this work will provide novel and comprehensive approaches for studying stochastic demography within this important model system and will provide insights into how the impact of treatments leading to increased longevity propagate throughout the reproductive lifespan of an individual.